Automated Parameter Selection for Total Variation Minimization in Image Restoration

@article{Langer2016AutomatedPS,
  title={Automated Parameter Selection for Total Variation Minimization in Image Restoration},
  author={Andreas Langer},
  journal={Journal of Mathematical Imaging and Vision},
  year={2016},
  volume={57},
  pages={239-268}
}
Algorithms for automatically selecting a scalar or locally varying regularization parameter for total variation models with an $$L^{\tau }$$ L τ -data fidelity term, $$\tau \in \{1,2\}$$ τ ∈ { 1 , 2 } , are presented. The automated selection of the regularization parameter is based on the discrepancy principle, whereby in each iteration a total variation model has to be minimized. In the case of a locally varying parameter, this amounts to solve a multiscale total variation minimization problem… CONTINUE READING

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